Machine Learning Engineer 2

Our Company
Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

Excited by AI/ML? Interested in creating new innovative solutions using Machine Learning. The Document Cloud team, in Noida, is creating PDF solutions spanning all surfaces - Web, Mobile, Desktop and Platform APIs, that processes billions of PDFs every month using ML, Deep-Learning and Generative AI at its core.

As a part of this, we need experienced individuals focusing on research and development of methods for processing huge amount of content, and can build mashups of Vision, Image Processing, NLP, generative models to solve complex problems.

• Develop algorithms that apply deep learning and state of the art methods in NLP & computer vision, combined with traditional large sophisticated solutions/codebases.
• Create experiments, algorithms and ship solution that not only yield high accuracy but are also designed and engineered to scale.
• Collaborate across multiple research and engineering disciplines, making the tradeoffs required to rapidly deliver AI/ML software solutions.

• B.Tech in Computer Science. MS/PhD preferred.
• 3+ years hands-on experience in either deep-learning models, Image processing, Vision and/or NLP.
• Ability to write efficient, clean, and reusable code in Python. Knowledge of C++ is preferred.
• Broad Machine Learning experience – Data, Modelling, Metric, Analysis of Results.
• Experience in using TensorFlow or PyTorch.
• Exposure to Deep Learning - CNNs, LSTMs, Transformers, network architecture, network tuning, transfer learning, multi-task learning.
• Exposure in building solutions from scratch and writing maintainable code inside large existing codebases.
• Strong software development skills that encourage code reuse among engineers and researchers.
• Experience in building AI applications for multiple locales will be preferred

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